A hierarchical framework for minimising emissions in hybrid gas-renewable energy systems under forecast uncertainty

IF 10.1 1区 工程技术 Q1 ENERGY & FUELS
Kiet Tuan Hoang , Christian Ankerstjerne Thilker , Brage Rugstad Knudsen , Lars Struen Imsland
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Abstract

Developing and deploying renewables in existing energy systems are pivotal in Europe’s transition to net-zero emissions. In this transition, gas turbines (GTs) will be central for balancing purposes. However, a significant hurdle in minimising emissions of GTs operating in combination with intermittent renewables arises from the reliance on unreliable meteorological forecasts. Here, we propose a hierarchical framework for decoupling this operational problem into a balancing and emissions minimisation problem. Balancing is ensured with a high-level stochastic balancing filter (SBF) based on data-driven stochastic grey-box models for the uncertain intermittent renewable. The filter utilises probabilistic forecasting and less conservative chance constraints to compute safe bounds, within which a proposed low-level economic predictive controller further minimises emissions of the GTs during operations. As GTs exhibit semi-continuous operating regions, complementarity constraints are utilised to fully exploit each GT’s allowed operational range. The proposed method is validated in simulation for a gas-balanced hybrid renewable system with batteries, three GTs with varying capacities, and a wind farm. Using real historical operational wind data, our simulation shows that the proposed framework balances the energy demand and minimises emissions with up to 4.35% compared with other conventional control strategies in simulation by minimising the GT emissions directly with complementarity constraints in the low-level controller and indirectly with less conservative chance constraints in the high-level filter. The simulations show that the computational cost of the proposed framework is well within requirements for real-time applications. Thus, the proposed operational framework enables increased renewable share in hybrid energy systems with GTs and renewable energy and subsequently contributes to de-carbonising these types of isolated or grid-connected systems onshore and offshore.

Abstract Image

在预测不确定的情况下尽量减少天然气-可再生能源混合能源系统排放的分层框架
在现有能源系统中开发和部署可再生能源是欧洲向净零排放过渡的关键。在这一过渡过程中,燃气轮机(GT)将成为平衡的核心。然而,由于依赖不可靠的气象预报,燃气轮机与间歇性可再生能源结合运行时在最大限度减少排放方面遇到了重大障碍。在此,我们提出了一个分层框架,将这一运行问题解耦为平衡和排放最小化问题。平衡问题通过高级随机平衡滤波器(SBF)来确保,该滤波器基于数据驱动的随机灰盒模型,用于不确定的间歇性可再生能源。该过滤器利用概率预测和不太保守的机会约束来计算安全边界,在此范围内,所建议的低级经济预测控制器可进一步将 GT 在运行期间的排放量降至最低。由于 GT 显示出半连续的运行区域,因此利用互补性约束来充分利用每个 GT 的允许运行范围。所提出的方法在一个带电池的气体平衡混合可再生能源系统、三个不同容量的发电机和一个风电场的模拟中得到了验证。通过使用真实的历史风力运行数据,我们的仿真结果表明,与其他传统控制策略相比,通过在低级控制器中直接使用互补性约束条件,以及在高级滤波器中间接使用不那么保守的偶然性约束条件,所提出的框架可以平衡能源需求,并将排放量降至最低,最高可达 4.35%。模拟结果表明,拟议框架的计算成本完全符合实时应用的要求。因此,所提出的运行框架能够提高 GTs 与可再生能源混合能源系统中的可再生能源比例,进而促进这些类型的陆上和海上孤立或并网系统的去碳化。
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来源期刊
Applied Energy
Applied Energy 工程技术-工程:化工
CiteScore
21.20
自引率
10.70%
发文量
1830
审稿时长
41 days
期刊介绍: Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.
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